Search Results
Simulation-Based Inference for Global Health Decisions
The COVID-19 pandemic has highlighted the importance of in-silico epidemiological modelling in predicting the dynamics of infectious diseases to inform health policy and decision makers about suitable prevention and containment strategies.
PerfectDou: Dominating DouDizhu with Perfect Information Distillation
To this end, we characterize card and game features for DouDizhu to represent the perfect and imperfect information.
Efficient and Scalable Graph Pattern Mining on GPUs
We describe G2Miner, the first Graph Pattern Mining (GPM) framework that runs on multiple GPUs.
Distributed, Parallel, and Cluster Computing
Optimal Decision Making Under Strategic Behavior
Using this characterization, we first show that, in general, we cannot expect to find optimal decision policies in polynomial time and there are cases in which deterministic policies are suboptimal.
An LSTM-Based Autonomous Driving Model Using Waymo Open Dataset
The Waymo Open Dataset has been released recently, providing a platform to crowdsource some fundamental challenges for automated vehicles (AVs), such as 3D detection and tracking.
Approximate information state for approximate planning and reinforcement learning in partially observed systems
Our key result is to show that if a function of the history (called approximate information state (AIS)) approximately satisfies the properties of the information state, then there is a corresponding approximate dynamic program.
Active Uncertainty Reduction for Safe and Efficient Interaction Planning: A Shielding-Aware Dual Control Approach
To ensure the safe operation of the interacting agents, we use a runtime safety filter (also referred to as a "shielding" scheme), which overrides the robot's dual control policy with a safety fallback strategy when a safety-critical event is imminent.
Learning Heuristic Search via Imitation
In this paper, we do so by training a heuristic policy that maps the partial information from the search to decide which node of the search tree to expand.
Active Uncertainty Reduction for Human-Robot Interaction: An Implicit Dual Control Approach
The ability to accurately predict human behavior is central to the safety and efficiency of robot autonomy in interactive settings.
Chat with the Environment: Interactive Multimodal Perception Using Large Language Models
However, it remains challenging to ground LLMs in multimodal sensory input and continuous action output, while enabling a robot to interact with its environment and acquire novel information as its policies unfold.
